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\begin{document}

\title{Transcriptomic responses in the nervous system and correlated
behavioural changes of a cephalopod exposed to ocean acidification}



\author[1,2]{Jodi Thomas}%
\author[2]{Roger Huerlimann}%
\author[3]{Celia Schunter}%
\author[4,5]{Sue-Ann Watson}%
\author[1]{Philip Munday}%
\author[2]{Timothy Ravasi}%
\affil[1]{Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland 4811, Australia}%
\affil[2]{Marine Climate Change Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan}%
\affil[3]{Swire Institute of Marine Science, School of Biological Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR}%
\affil[4]{College of Science and Engineering, James Cook University, Townsville, Queensland 4811, Australia}%
\affil[5]{Biodiversity and Geosciences Program, Museum of Tropical Queensland, Queensland Museum Network, Townsville, Queensland 4810, Australia}%


\vspace{-1em}



  
  \date{May 30, 2024}


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\selectlanguage{english}
\begin{abstract}
The nervous system is central to coordinating behavioural responses to
environmental change, likely including ocean acidification (OA).
However, a clear understanding of neurobiological responses to OA is
lacking, especially for marine invertebrates. We evaluated the
transcriptomic response of the central nervous system (CNS) and eyes of
the two-toned pygmy squid (\emph{Idiosepius pygmaeus}) to OA conditions,
using a \emph{de novo} transcriptome assembly created with long read
PacBio ISO-sequencing data. We then correlated patterns of gene
expression with CO\textsubscript{2} treatment levels and OA-affected
behaviours in the same individuals. OA induced transcriptomic responses
within the nervous system related to various different types of
neurotransmission, neuroplasticity, immune function and oxidative
stress. These molecular changes may contribute to OA-induced behavioural
changes, as suggested by correlations between gene expression profiles,
CO\textsubscript{2} treatment and OA-affected behaviours. This study
provides the first molecular insights into the neurobiological effects
of OA on a cephalopod and correlates molecular changes with whole animal
behavioural responses, helping to bridge the gap in our knowledge
between environmental change and animal responses.%
\end{abstract}%



\sloppy


\par\null

\textbf{1. Introduction}

As human-induced environmental changes progress, establishing how
animals respond to projected future environmental conditions, and why
these responses occur, is critical (Fuller \emph{et al.}, 2010). A
thorough understanding of why biological responses are occurring is
especially useful for gaining insight into why some individuals or
species are more sensitive to environmental change than others, and
improving predictions of how organisms and populations will respond over
the time scales at which environmental change is occurring
(Cooke~\emph{et al.}, 2013). The nervous system forms the fundamental
link between the environment and an animal's responses (Kelley \emph{et
al.}, 2018; O'Donnell, 2018). Thus, the neurobiological impacts of
anthropogenic environmental change are key to understanding how animals
will respond as environmental change progresses, yet the role of the
nervous system in biological responses to environmental change has been
little explored (Kelley \emph{et al.}, 2018).

The uptake of anthropogenic carbon dioxide (CO\textsubscript{2}) by the
ocean is causing seawater CO\textsubscript{2} levels to rise, decreasing
seawater pH and altering the concentration of carbonate ions, in a
process known as ocean acidification (OA) (Bindoff \emph{et al.}, 2019).
These chemical changes can fundamentally affect marine organisms and the
ecosystems they inhabit (Doney \emph{et al.}, 2009). OA affects a wide
variety of physiological processes, life history traits and behaviours
of marine invertebrates (Durant \emph{et al.}, 2023; Kroeker \emph{et
al.}, 2010; Nagelkerken \& Connell, 2015; P\selectlanguage{ngerman}örtner \emph{et al.}, 2004;
Thomas \emph{et al.}, 2020). Invertebrates are vital components of
marine ecosystems, comprising over 92\% of species in the ocean, are
essential to the function of ecosystem processes, and support the
livelihoods of human societies across the globe (Bertness \emph{et al.},
2001; Chen, 2021). Animal behaviour influences an individual's own
fitness, complex interactions with other individuals and species, and
key ecological processes that shape the structure of marine communities
and ecosystems (Nagelkerken \& Munday, 2015). Consequently, any
behavioural effects of elevated CO\textsubscript{2} on marine
invertebrates could potentially have wide-ranging ecological, social and
economic consequences.

Despite many studies assessing the behavioural responses of marine
invertebrates to OA the link between the environment and behavioural
responses, the nervous system, has been largely understudied. The work
that has addressed the neurobiological impacts of OA has focused on the
functioning of GABA\textsubscript{A} receptors. The GABA hypothesis was
first proposed in fish and suggests acid-base regulatory mechanisms
occurring at elevated CO\textsubscript{2} conditions alter ionic
gradients across neuronal membranes, consequently disturbing
GABA\textsubscript{A} receptor function and causing behavioural
alterations (Nilsson \emph{et al.}, 2012). A range of research has
supported the GABA hypothesis in fish (reviewed in Heuer \emph{et
al.~}(2019)), and more recently pharmacological studies have also
supported the GABA hypothesis in molluscs (Clements \emph{et al.}, 2017;
Thomas~\emph{et al.}, 2021; Watson \emph{et al.}, 2014), but not a
crustacean (Charpentier \& Cohen, 2016). However, OA may also have a
range of other neurobiological impacts, including altering the function
of other ligand-gated ion channels that are similar to the
GABA\textsubscript{A~}receptor (Thomas \emph{et al.}, 2021) and
affecting synaptic plasticity (Lai \emph{et al.}, 2017; Porteus \emph{et
al.}, 2018).

Transcriptomics provides a powerful non-targeted, holistic approach to
identify functional responses to environmental change. Indeed,
transcriptomics has widely been taken up by the OA research community to
understand the response of marine animals to elevated
CO\textsubscript{2} (Strader \emph{et al.}, 2020). However, there is
less research assessing the transcriptomic response of nervous tissue to
elevated CO\textsubscript{2}. Recently, studies have examined the
transcriptomic response of the fish nervous system to elevated
CO\textsubscript{2} conditions, including in coral reef fishes
(Kang~\emph{et al.}, 2022; Schunter \emph{et al.}, 2021; Schunter
\emph{et al.}, 2019; Schunter \emph{et al.}, 2018; Schunter \emph{et
al.}, 2016), temperate marine fishes (Cohen-Rengifo \emph{et al.}, 2022;
Porteus~\emph{et al.}, 2018; Toy \emph{et al.}, 2022) and ocean-phase
salmon (Williams \emph{et al.}, 2019). In marine invertebrates, two
transcriptomic studies assessing the whole-body response of pteropod
molluscs to elevated CO\textsubscript{2} identified altered expression
of genes involved in nervous system function (Johnson \& Hofmann, 2017;
Moya \emph{et al.}, 2016). However, whole body measurements cannot
determine if non-tissue-specific transcripts are responding to elevated
CO\textsubscript{2} in a system-wide manner, or only within specific
tissues. Furthermore, due to the heterogeneity and complexity of gene
expression, measurements at the whole-body level may mask transcriptomic
responses in specific tissues, such as the nervous system.

Here, we investigated the transcriptomic response to OA in the central
and peripheral nervous system of a cephalopod, the two-toned pygmy squid
(\emph{Idiosepius pygmaeus} ), and then correlated the molecular
responses with behavioural changes recorded in the same individuals.
Cephalopods have complex nervous systems and behaviours rivalling those
of fishes (Hanlon \& Messenger, 2018), making them a useful taxon to
investigate the neurobiological impacts of elevated
CO\textsubscript{2}.~\emph{I. pygmaeus} is a diurnal, tropical squid
inhabiting shallow, inshore waters of the Indo-Pacific, including
Northern and North-eastern Australia (Moynihan, 1983; Reid, 2005). They
are a small, short-lived squid growing to a maximum mantle length of 2
cm (Reid, 2005), and have a lifespan of up to 80 days (Jackson, 1988).
\emph{I. pygmaeus} is an ideal species to use as previous research in
this species found elevated CO\textsubscript{2} alters a range of
behaviours (Spady \emph{et al.}, 2018; Spady \emph{et al.}, 2014; Thomas
\emph{et al.}, 2021).

In this study, we used RNA from the central nervous system (CNS) and
eyes (peripheral sense organ) from squid exposed to current-day
(\textasciitilde{}400 \selectlanguage{greek}µ\selectlanguage{english}atm) or elevated (\textasciitilde{}1,000 \selectlanguage{greek}µ\selectlanguage{english}atm)
CO\textsubscript{2} levels for 7 days in a previous study by
Thomas~\emph{et al.} (2021). In these squid, elevated
CO\textsubscript{2~}exposure increased activity levels as well as
visually-guided, conspecific-directed attraction and aggression (Thomas
\emph{et al.}, 2021). Here, we created a \emph{de novo} transcriptome
assembly, providing a reference which we used to determine the
transcriptomic response of the squid CNS and eyes to elevated
CO\textsubscript{2}. We used the eyes because cephalopods, including
squid, are highly visual animals with many visually-guided behaviours
(Chung \emph{et al.}, 2022; Mather, 2006; Muntz, 1999). Furthermore, we
have shown elevated CO\textsubscript{2}-induced disturbances of
visually-guided behaviour in the same squid used in this study (Thomas
\emph{et al.}, 2021). As we had transcriptomic and behavioural data from
the same individual squid, we also correlated patterns of gene
expression with CO\textsubscript{2~}treatment levels and OA-affected
behaviours to determine key genes and processes in the cephalopod CNS
and eyes potentially contributing to OA-induced behavioural changes. The
results from this study help us understand, at a molecular level, the
neurobiological impacts of ocean acidification in a marine invertebrate
with a complex nervous system.

\textbf{2. Methods}

2.1 Animal collection and experimental setup

The squid tissues and behavioural data used in this study came from a
previous experiment. Specifically, we used sham-treated squid from the
picrotoxin experiment in Thomas \emph{et al.} (2021) (Figure 1). As
described in Thomas \emph{et al.} (2021), male two-toned pygmy squid
(\emph{Idiosepius pygmaeus}) were collected from the wild and acclimated
in groups at current-day seawater conditions for 1 - 6 days before
transferral to individual treatment tanks set at either current-day
(\textasciitilde{}400 \selectlanguage{greek}µ\selectlanguage{english}atm) or elevated (\textasciitilde{}1,000 \selectlanguage{greek}µ\selectlanguage{english}atm)
CO\textsubscript{2} levels, consistent with CO\textsubscript{2} levels
projected for 2100 following the representative concentration pathway
RCP8.5 scenario (Bindoff \emph{et al.}, 2019). Experiments were carried
out in four interconnected 8,000 L recirculating seawater systems; two
untreated seawater systems were used for current-day
CO\textsubscript{2}treatments, and two seawater systems were dosed with
CO\textsubscript{2~}using a custom-built pH control system for elevated
CO\textsubscript{2}treatments. The CO\textsubscript{2} conditions
achieved were current-day CO\textsubscript{2}: 407 \selectlanguage{ngerman}± 58 \selectlanguage{greek}µ\selectlanguage{english}atm
\emph{p}CO\textsubscript{2}, pH\textsubscript{T} = 8.09 \selectlanguage{ngerman}± 0.10 and
elevated CO\textsubscript{2}: 1,071 ± 71 \selectlanguage{greek}µ\selectlanguage{english}atm
\emph{p}CO\textsubscript{2}, pH\textsubscript{T} = 7.73 \selectlanguage{ngerman}± 0.03 (mean ±
SD). Refer to Thomas \emph{et al.} (2021) for further details.
CO\textsubscript{2} variation is common in coastal habitats (Hannan
\emph{et al.}, 2020). However, the coastal waters where we collected
\emph{I. pygmaeus} show little daily variation in
seawater~\emph{p}CO\textsubscript{2} levels; average daily range 20.3 ±
8.6 \selectlanguage{greek}µ\selectlanguage{english}atm CO\textsubscript{2} (mean \selectlanguage{ngerman}± SD) (Supplementary Text S1 and
Figure S1). Thus, our experimental CO\textsubscript{2} levels are
ecologically relevant to the population of \emph{I. pygmaeus} used.

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1-experimental-design/Figure-1-experimental-design}
\caption{{\textbf{Experimental design overview.} CCA = canonical correlation
analysis. \emph{Idiosepius pygmaeus} photograph by Jodi Thomas.
{\label{864034}}%
}}
\end{center}
\end{figure}

2.2 Behavioural analysis

After 7 days of current-day or elevated CO\textsubscript{2} treatment,
squid underwent sham treatment by being individually placed in 100 mL of
aerated seawater from their CO\textsubscript{2} treatment containing
0.2\% ethanol for 30 minutes, as part of the experiment by
Thomas~\emph{et al.} (2021). Visually-guided behaviour was then tested
for 15 minutes by placing squid individually in a tank (30\selectlanguage{ngerman}×30×15 cm)
filled to 3 cm depth with seawater from their CO\textsubscript{2}
treatment and with a mirror taking up the entire area of one wall. Three
aspects of squid behaviour shown to be altered by elevated
CO\textsubscript{2} in Thomas \emph{et al.} (2021), activity level,
aggressive conspecific-directed behaviour and exploratory
conspecific-directed behaviour (Table 1), were used here. See Thomas
\emph{et al.} (2021) for a detailed description of the behavioural
analysis and results.

2.3 Tissue sample collection

Immediately after each behavioural trial, squid were euthanised with
AQUI-S (1:1000). The head was separated from the mantle, rinsed in
distilled water, and blotted dry. The skin, tentacles, beak, and buccal
mass were removed and the eyes and central nervous system (CNS,
containing the oesophagus running through the middle) were dissected and
snap frozen in liquid nitrogen within 4.18 ± 0.55 (mean ± SD) minutes
after euthanasia. Tissues were then transferred to
-80\textsuperscript{O}C for storage. This study followed the animal
ethics guidelines at James Cook University (JCU animal ethics number
A2644).

2.4 RNA extraction

Total RNA was extracted from the entire CNS, and both eyes combined for
each squid (n\textsubscript{current-day CO2} = 10,
n\textsubscript{elevated CO2} = 10 for each tissue) (Figure 1). Each
tissue sample was homogenised in RLT-Plus Buffer (Qiagen) with sterile
zirconia/silica beads (1mm diameter, BioSpec Products) in a
Mini-BeadBeater 96 (BioSpec Products) for a total of 2 minutes. Total
RNA was extracted using an AllPrep DNA/RNA Mini Kit (Qiagen). RNA
integrity of all 40 samples was measured on an Agilent 2200 TapeStation
(High Sensitivity RNA ScreenTape, Agilent) (Supplementary File S1).

2.5 RNA sequencing

The Sequencing Section, Okinawa Institute of Science and Technology
Graduate University, Japan carried out library preparation and
sequencing on all 40 RNA samples. RNA was quantified by Qubit Flex
Fluorometer (Qubit RNA BR assay kit, Thermo Fisher Scientific Inc.). The
NEBNext® Poly(A) mRNA Magnetic Isolation Module (New England BioLabs
Inc.) was followed according to the manufacturers protocol to isolate
mRNA. One library was prepared for each sample, using the NEBNext® Ultra
II Directional RNA Library Prep Kit for Illumina® (New England BioLabs
Inc.) following the manufacturers protocol, using ten PCR cycles.
Libraries were sequenced on two lanes of a NovaSeq6000 with a S2 flow
cell paired end to the length of 150 bp.

2.6 RNA-seq read pre-processing

For a detailed workflow of the bioinformatic and statistical analyses,
see Supplementary Figure S2. Raw reads were inspected with FastQC
(v0.11.9) (Andrews, 2010) and MultiQC (v1.9) (Ewels \emph{et al.}, 2016)
and trimmed with Fastp (v0.21.1) (Chen \emph{et al.}, 2018) using a
sliding window of 4 bp, a mean Phred score of 30 and reads \textless{}
30 bp were trimmed. Kraken2 (v2.0.9) (Wood \emph{et al.}, 2019) was used
with a confidence of 0.3 to remove any contamination using the NCBI
bacterial and archaeal reference libraries (downloaded 08/2020).

2.7 Read mapping and counting

As a reference for gene expression quantification, we created and
annotated a \emph{de novo} transcriptome assembly of \emph{I.
pygmaeus~}CNS and eye tissues using long read PacBio ISO-sequencing
data. Refer to Supplementary Text S2 for a description of the methods
for ISO-sequencing, \emph{de novo} transcriptome assembly, and
transcriptome annotation. The trimmed and decontaminated RNA-seq reads
were mapped against the transcriptome assembly using salmon (v1.3.0)
(Patro \emph{et al.}, 2017). Correction for sequence-specific biases and
fragment-level GC biases was used, the quantification step was skipped,
and the flags `--validateMappings' and `--hardFilter' were also used.
Corset (v1.09) (Davidson \& Oshlack, 2014) was run on the salmon
equivalence class files from all 40 samples to cluster the transcripts
to gene-level and produce gene-level counts. In Corset, we provided the
four groups/treatments (eyes current-day CO\textsubscript{2}, eyes
elevated CO\textsubscript{2}, CNS current-day CO\textsubscript{2} and
CNS elevated CO\textsubscript{2}), the log likelihood ratio test was
switched off to prevent differentially expressed transcripts being split
into different clusters, and the links between contigs were removed if
the link was supported by less than 10 reads.

2.8 Statistical analyses

All statistical analyses (as described below) were carried out in R
(v4.0.4) (R Core Team, 2021), primarily using RStudio (v 1.4.1106)
(RStudio Team, 2021).

2.8.1 Differential expression analysis

DESeq2 (v1.30.1) (Love \emph{et al.} , 2014) using the Wald test was
used to compare gene expression between current-day and elevated
CO\textsubscript{2} conditions for the CNS and eyes separately. Genes
with an adjusted p-value (padj, Benjamini-Hochberg method) \textless{}
0.05 were reported as differentially expressed (DE). Log2fold change
estimates were shrunk with the ashr method (Stephens, 2016) to increase
their accuracy.

2.8.2 Gene set enrichment analysis

Gene set enrichment analysis (GSEA) was run in clusterProfiler (v3.18.1)
(Yu \emph{et al.}, 2012) for each tissue separately to determine if sets
of genes from the same gene ontology (GO) term/functional category
showed significant, concordant differences between current-day and
elevated CO\textsubscript{2} conditions. Unweighted GSEA was run using
the DESeq2 log2 fold-change values of all genes and the annotated GO
terms as the `gene sets'. A minimum and maximum gene set size of 15 and
500, respectively, was used. GSEA determines if genes from the same
functional category are significantly more likely to occur at the top or
bottom of the log2 fold-change list and therefore whether these
functional categories are up- or down-regulated at elevated
CO\textsubscript{2}, respectively. P-values were adjusted for multiple
comparisons using the Benjamini-Hochberg method and a significance
threshold of padj \textless{} 0.05 was used. The GSEA results were
imported into Cytoscape (v3.8.2) (Shannon \emph{et al.}, 2003) where
EnrichmentMap (v3.3.1) (Merico \emph{et al.}, 2010) was used to create a
network to visualise the functional enrichment results. All significant
functional categories were included in the network as a circular node.
Functional categories with \textgreater{} 0.25 similarity were linked by
edges. Similar functional categories were manually grouped into clusters
and labelled.

2.8.3 Correlating gene expression profiles with CO\textsubscript{2}
treatment and OA-affected behaviours

To analyse the correlation between gene expression and behavioural
traits of squid across CO\textsubscript{2} treatments, we employed
weighted gene co-expression network analysis (WGCNA) followed by
canonical correlation analysis (CCA) on the CNS and eyes, separately
(Figure 1). Refer to Supplementary Text S3 for a detailed description of
the methods for gene co-expression network construction and module
detection, module eigengene correlation with behavioural traits, module
membership vs gene significance, and identification of hub genes
(Figures S3 -- S21, Tables S1 and S2). Briefly, the gene-level counts
from DESeq2 (v1.30.1) (Love \emph{et al.}, 2014) were used in the WGCNA
package (v1.70-3) (Langfelder \& Horvath, 2008) to construct a
co-expression network and detect modules of genes. A module eigengene
was calculated for each module of genes, representing the gene
expression profiles of that module. CCA using package CCA (v1.2.1)
(González \emph{et al.}, 2008)~was used to explore the correlations
between the two sets of variables from the same individual squid: ME set
= module eigengenes from each module; traits set =
CO\textsubscript{2~}level (current-day or elevated) and behavioural
traits (active time (s), distance (cm), speed (cm/s), time in Zone A
(s), whether the squid displayed an exploratory/aggressive interaction
(yes/no), number of exploratory/aggressive interactions). For those
modules identified by CCA to be correlated with each trait, the Pearson
correlation of module membership (MM, higher value indicates the gene is
more highly connected to the given module) and gene significance (GS,
higher value indicates a more biologically relevant gene) was calculated
(Langfelder \& Horvath, 2008). A correlation of GS and MM imply that
genes more highly connected with a given module also tend to be more
highly correlated with the given trait, providing another measure for
the importance of this module with the given trait (Langfelder \&
Horvath, 2008). This identified the final modules of interest, within
which the MM and GS values of each gene were used as a screening method
to identify biologically relevant, highly interconnected hub genes
(Fuller \emph{et al.}, 2007; Horvath \& Dong, 2008; Langfelder \&
Horvath, 2008), i.e. to find genes correlated with CO\textsubscript{2}
treatment and each behavioural trait. Hub genes were defined as those
genes within the final modules of interest with a very strong
correlation with the module (MM \textgreater{} 0.8) and a moderate
correlation with the given trait (GS \textgreater{} 0.4).

All hub genes for CO\textsubscript{2} treatment were compared across
tissues to identify hub genes for CO\textsubscript{2} treatment that are
CNS-specific, eyes-specific or found in both tissues. Hub genes for
CO\textsubscript{2} treatment that were also a hub gene for one or more
behavioural traits were identified as genes correlated with the
associated OA-induced behavioural change. Finally, functional enrichment
analysis was used for the CNS-specific CO\textsubscript{2} treatment hub
genes that were also hub genes for all three activity traits in the CNS
using over-representation analysis (ORA) in clusterProfiler (v3.18.1)
(Yu \emph{et al.}, 2012) with the hypergeometric test. This determined
if any GO terms were significantly over-represented within the list of
hub genes. All other groups of CO\textsubscript{2} treatment hub genes
had 25 or fewer genes and thus ORA was not used. P-values were adjusted
for multiple comparisons using the Benjamini-Hochberg method and a
significance threshold of padj \textless{} 0.05 was used.

\textbf{3. Results}

3.1 Transcriptome assembly and annotation

The \emph{de novo} transcriptome assembly for \emph{Idiosepius
pygmaeus~}was created from a total of 138.6 million PacBio
ISO-sequencing subreads and resulted in 49,981 transcripts that were
clustered into 27,420 genes. The transcriptome assembly had an N50 of
3,163 bp, 70.4\% complete BUSCOs and an 82.1 ± 5.5\% overall alignment
rate of the RNA-seq reads (Table S3). A total of 69\% of the transcripts
received a functional annotation (Supplementary Table S4). The species
distribution of the top blast hits was dominated by cephalopod species
(Figure S22). Final mapping of RNA-seq reads against the transcriptome
assembly had a 73.6 ± 6.9\% mapping rate (Table S5).

3.2 Differentially expressed genes

We compared gene expression between current-day and elevated
CO\textsubscript{2} conditions for the CNS and eyes separately. There
was more variance in the eyes than the CNS (Figure 2A). In the CNS, we
identified 25 differentially expressed genes (DEGs) between current-day
and elevated CO\textsubscript{2} conditions; 14 upregulated and 11
downregulated with elevated CO\textsubscript{2}. In the eyes, there were
eight DEGs; five upregulated and three downregulated at elevated,
compared to current-day, CO\textsubscript{2} conditions (Figure 2B). Two
genes were significantly upregulated with elevated
CO\textsubscript{2~}in both the CNS and eyes; one essential for
autophagy (\emph{ykt6}) and another poorly characterised gene
(\emph{fam204a}). In both tissues, the DEGs play roles in
neurotransmission (CNS: \emph{folh1}, \emph{syvn1-b},~\emph{slc2a13},
\emph{celsr3}, eyes: \emph{maoa}, \emph{slc18a1},~\emph{cbs}), immune
function (CNS: \emph{psenen}, \emph{syvn1}-\emph{b, map4k5}, \emph{tf},
\emph{nme6}, \emph{map1l3ca/b}, eyes: \emph{pglyrp2},~\emph{cbs, maoa}),
the oxidative stress response (CNS: \emph{tf},~\emph{cyb561d2, syvn1-b},
\emph{chrac1, ykt6}, eyes: \emph{cbs, ykt6}), and transcription
regulation (CNS: \emph{nme6, chrac1, znf271}, eyes:~\emph{gtf2e2} )
(Table S6).

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2-PCA-DEVenn-GSEAVenn-smaller/Figure-2-PCA-DEVenn-GSEAVenn-smaller}
\caption{{~\textbf{Differential expression and GSEA results. A} PC1 and PC2 axes
from the principal components analysis of all genes for the 40
samples.~\textbf{B~}Venn diagram comparing the DEGs between current-day
and elevated CO\textsubscript{2} levels in the CNS and eyes.~\textbf{C
~}Venn diagram comparing the GO terms / functional categories found to
be significantly different between current-day and elevated
CO\textsubscript{2} levels in the CNS and eyes by GSEA. circle = CNS
current-day, square = CNS elevated CO\textsubscript{2}, diamond = Eyes
current-day, triangle = Eyes elevated CO\textsubscript{2}, | =
upregulated at elevated CO\textsubscript{2} conditions, | =
downregulated at elevated CO\textsubscript{2} conditions. ~
{\label{231350}}%
}}
\end{center}
\end{figure}

3.3 Small, coordinated changes in expression of genes belonging to the
same functional categories

Gene set enrichment analysis (GSEA) identified Gene Ontology (GO)
terms/functional categories, across all three GO categories (biological
process, molecular function, and cellular component), that were
significantly affected by CO\textsubscript{2} treatment, indicating
small, coordinated changes in expression of the genes belonging to each
of these functional categories. We identified ninety-nine significant
functional categories in the CNS; 75 upregulated and 24 downregulated at
elevated CO\textsubscript{2} (Figure 2C). These functional categories
included those involved in transcription, RNA processing, translation,
protein processing, the cell cycle and cell proliferation, and
neurotransmission (Figures 3 and S23). There were 17 significant
functional categories in the eyes; 12 upregulated and 5 downregulated at
elevated CO\textsubscript{2} (Figure 2C). Ten functional categories were
significantly affected by CO\textsubscript{2} treatment in both the CNS
and eyes including functions related to the ribosome and translation,
ion channels, kinase activity, protein degradation and cell adhesion
(Figures 3 and S23).

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/GSEA-CNS-Eyes-for-combined-paper-2/Figure-3-enrichment-map-GSEA}
\caption{{~\textbf{Enrichment map displaying the gene set enrichment analysis
(GSEA) results in both the CNS and eyes.~} Significant GO
terms/functional categories are represented by a circular node. Results
from the CNS and eyes are represented by colouration of the inner node
area and node border, respectively. Red represents functional categories
upregulated at elevated CO\textsubscript{2} and blue represents
functional categories downregulated at elevated CO\textsubscript{2}.
Colour intensity represents the normalised enrichment score and node
size the number of core enrichment genes in each functional category.
{\label{530450}}%
}}
\end{center}
\end{figure}

3.4 Genes correlated with OA-induced behavioural change

We identified 230 and 25 hub genes for CO\textsubscript{2} treatment in
the CNS and eyes, respectively, with 14 CO\textsubscript{2} treatment
hub genes shared by both tissues. Of these CO\textsubscript{2} treatment
hub genes in the CNS, eyes and both tissues, 169, 6 and 10 genes were
also identified as hub genes for one or more behavioural traits,
respectively, indicating these genes as potentially correlated with
CO\textsubscript{2}-induced behavioural changes (Figure 4). Of the 169
genes in the CNS potentially contributing to CO\textsubscript{2}-induced
behavioural changes, 87 were positively correlated with
CO\textsubscript{2} treatment and all three activity traits and were
significantly enriched for 13 functional categories, including those
playing a role in the cell cycle, cell migration, and protein synthesis
and folding (Figure 5). Four of these functional categories were also
identified as significantly upregulated at elevated
CO\textsubscript{2~}in the CNS by GSEA; `nuclear pore', `motor
activity', `chromosome' and `protein kinase binding'. The six
transcripts in the eyes potentially contributing to
CO\textsubscript{2}-induced behavioural changes had a match for two
known genes; an acetylcholine receptor subunit (\emph{chrna10}) and a
gene essential for maintaining retinal tissue integrity (\emph{crb}).
The 10 transcripts in both tissues potentially contributing to
CO\textsubscript{2}-induced behavioural changes had a match for eight
known genes, again including~\emph{chrna10,} and genes with putative
roles in cell proliferation (\emph{gid-4, cdk10}) and protein processing
(\emph{srp72, vhl, zranb1}). See Table S7 -- S10 for all hub genes
identified by WGCNA and their putative functions.

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-4/Figure-4}
\caption{{~\textbf{Venn diagram depicting the number of hub genes identified for
CO}\textsubscript{\textbf{2}} \textbf{treatment and behavioural traits
in the CNS and eyes.~} The yellow Venn diagram in the centre depicts the
number of hub genes for CO\textsubscript{2} treatment that are
CNS-specific (left) and eyes-specific (right), and the overlap
represents the number of CO\textsubscript{2} treatment hub genes shared
by both tissues. CNS-specific and eyes-specific CO\textsubscript{2}
treatment hub genes also identified as a hub gene for one or more
behavioural traits in the CNS or eyes are on the left and right,
respectively.~ Hub genes for CO\textsubscript{2} treatment found in both
tissues, that are also a hub gene for a behavioural trait in one or both
tissues, are shown at the bottom centre. CO\textsubscript{2} treatment
hub genes shared with activity traits (active time, distance and speed)
and exploratory conspecific-directed behaviours (number of exploratory
interactions and whether any exploratory interactions occurred) are in
blue and grey, respectively. Exploratory interaction? = whether any
exploratory interactions occurred (yes/no). ~
{\label{746528}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-5/Figure-5}
\caption{{\textbf{GO Terms/functional categories significantly enriched from the
87 genes positively correlated with CO}\textsubscript{\textbf{2}}
\textbf{treatment and all three activity traits in the CNS.} padj =
adjusted p-value, blue indicates higher significance. Gene Ratio = the
number of genes represented in the genes positively correlated with
CO\textsubscript{2} treatment and all three activity traits in the CNS,
in comparison to all of the genes in the CNS.
{\label{991492}}%
}}
\end{center}
\end{figure}

3.5 OA-affected genes and their functions

Genes affected by elevated CO\textsubscript{2} and correlated with
OA-induced behavioural change were identified in seven main functions:
neurotransmission; cell cycle; cell proliferation and differentiation;
neural wiring; transcription, RNA processing and protein processing;
immune function; oxidative stress.

3.5.1 Neurotransmission

A range of genes and functional categories involved in various types of
neurotransmission were significantly affected by
CO\textsubscript{2~}treatment (Table 2). We identified small,
coordinated downregulation of genes belonging to a cluster of nine
functional categories in the CNS, and upregulation of two functional
categories in the eyes, involved in ligand-gated ion channel-mediated
neurotransmission. The genes contributing most to the
up-/down-regulation of each of these functional categories (core
enrichment genes) in the CNS and eyes included genes for components of
acetylcholine, GABA\textsubscript{A} and glutamate ion channel receptors
(Table S11). There was also small, coordinated downregulation in the CNS
of genes belonging to two functional categories involved in G
protein-coupled receptor (GPCR)-mediated neurotransmission, including
genes coding for components of metabotropic glutamate,
GABA\textsubscript{B}, serotonin and dopamine receptors (Table S12).
Notably, a subunit of nicotinic acetylcholine receptors (\emph{chrna10})
was correlated with CO\textsubscript{2} treatment and behaviours in both
tissues. \emph{Chrna10} as well as other genes coding for nicotinic
acetylcholine receptor subunits (\emph{chrna1},~\emph{chrna3},
\emph{chrna5}, and \emph{chrnb1}) were core enrichment genes in eight
functional categories significantly affected by CO\textsubscript{2}
treatment in both tissues. Genes coding for regulation of GABAergic
neurotransmission were upregulated in both tissues (CNS: \emph{syvn1-b},
eyes: \emph{slc18a2}), and positively correlated with
CO\textsubscript{2} treatment and behaviours in the CNS (\emph{phf24},
\emph{rac1}), while \emph{aldh5a1}, which is involved in the final
degradation step of GABA (Kim \emph{et al.} , 2009), was negatively
correlated with CO\textsubscript{2} treatment and behaviours in the CNS.
Furthermore, there was upregulation of \emph{folh1}(glutamate synthesis)
and downregulation of \emph{celsr3} (mediator of glutamatergic synapse
formation) in the CNS. There was also upregulation in the eyes of two
key genes involved in monoaminergic (dopamine, serotonin (5-HT),
norepinephrine, and epinephrine) neurotransmission (\emph{maoa,
slc18a2}).

Genes involved in the general processes required for synaptic
neurotransmission also displayed altered expression after elevated
CO\textsubscript{2} exposure (Table 2). There was small, coordinated
downregulation in the CNS of genes belonging to a cluster of seven
functional categories involved in K\textsuperscript{+},
Ca\textsuperscript{2+} and Na\textsuperscript{+} ion transport important
for general processes involved in neurotransmission, including
maintenance of membrane potential, action potential generation and
neurotransmitter release (Table S13). Furthermore, genes involved in
regulating synaptic neurotransmission (\emph{futsch}, \emph{dgkq}) were
negatively correlated with CO\textsubscript{2} treatment and activity
traits in the CNS.

3.5.2 Cell cycle

In the CNS, we found small, coordinated upregulation of genes belonging
to functional categories involved in the cell cycle, and genes
positively correlated with CO\textsubscript{2} treatment and all three
activity traits were enriched for cell cycle functional categories
(Table 3, Figures 3 and 5). This included genes and functional
categories involved in regulating the cell cycle, as well as those
specifically involved in the cell cycle stages of interphase and
mitosis. In particular, there was small, coordinated upregulation of
genes belonging to the functional categories `chromosome' and `protein
kinase binding' (Figure 3), and these same functions were enriched in
the genes positively correlated with CO\textsubscript{2} treatment and
all three activity traits (Figure 5).

3.5.3 Cell proliferation and differentiation

Genes involved in cell proliferation and differentiation, including
specifically for neuronal differentiation and neurogenesis were mostly
positively correlated with CO\textsubscript{2} treatment and behaviours
in the CNS (Table 3). Genes involved in neuronal differentiation
(\emph{ttc3}), neural stem cell self-renewal (\emph{srrt}), neural
progenitor proliferation (\emph{melk}), and neurogenesis (\emph{ncaph,
adgrb3}) were all positively correlated with
CO\textsubscript{2~}treatment and activity traits. \emph{Bcar3}, which
promotes cell proliferation, migration and redistribution of actin
fibres, and~\emph{psap}, which acts as a neurotrophic and myelinotrophic
factor, were negatively correlated with CO\textsubscript{2} treatment
and positively correlated with number of exploratory interactions in the
CNS. Several \emph{cdk10} transcripts were identified as correlated with
CO\textsubscript{2}-induced behavioural change. \emph{Cdk10} codes for a
protein kinase that plays pivotal roles in controlling a range of
fundamental cellular processes including cell proliferation and
neurogenesis (reviewed in Guen \emph{et al.} (2017)).

3.5.4 Neural wiring

A range of genes and functional categories involved in neural wiring,
including cell migration and adhesion, and neurite growth and synapse
formation were affected by CO\textsubscript{2} treatment, also mostly
exhibiting an upregulation in the CNS (Table 3). There was small,
coordinated upregulation of genes involved in cell migration functional
categories, including `motor activity', `actin binding', `cell adhesion'
and `integrin complex'. Those genes positively correlated with
CO\textsubscript{2} treatment and all three activity traits in the CNS
were enriched for similar functional categories: `actin filament
binding', `myosin complex', `myofibril', `motor activity' and `ruffle
membrane'. Genes with a role specifically in neuron migration and
adhesion, and the related processes of dendrite and axon outgrowth and
branching, dendritic spine formation, and synapse formation were also
positively correlated with CO\textsubscript{2} treatment and activity
(\emph{rac1}, \emph{ptpr, adgrb3, apbb1}). One gene involved in neurite
growth and branching (\emph{futsch}) was negatively correlated with
CO\textsubscript{2} treatment and activity traits.

3.5.5 Transcription, RNA processing, and protein processing

There was generally an upregulation of genes and functional categories
involved in transcription, RNA processing and protein processing in the
CNS, and to a smaller extent in the eyes (Table 4). In the CNS, there
was small, coordinated upregulation of genes belonging to functional
categories involved in transcription, including `DNA duplex unwinding',
and its' daughter term `3'-5' DNA helicase activity' was enriched in
those genes positively correlated with CO\textsubscript{2} treatment and
all three activity traits (Figure 5). There was small, coordinated
upregulation in the CNS of genes belonging to the functional category
`nuclear pore', and `nuclear pore' was also enriched for those genes
positively correlated with CO\textsubscript{2} treatment and all three
activity traits in the CNS (Figure 5). Genes involved in transcription
were also DE; \emph{nme6, chrac1} and \emph{znf271} were upregulated in
the CNS, and \emph{gtf2e2} downregulated in the eyes. There was small,
coordinated upregulation of genes involved in `RNA processing', `mRNA
processing' and `rRNA processing', as well as functional categories
involved in the processes and components of the spliceosome, which
excises introns to produce mature mRNA (Figure 3). Components of the
spliceosome (\emph{snrpa}, \emph{snrnp200}) were also identified as
correlated with CO\textsubscript{2} treatment and behaviours (Table 4).

A range of genes and functional categories involved in protein
synthesis, folding and degradation/turnover were significantly
upregulated in the CNS, and some were also upregulated in the eyes.
Small, coordinated upregulation of genes involved in the initiation and
process of translation as well as in functional categories for ribosomal
components occurred in both tissues (Figure 3). Genes with similar
functions were also positively correlated with
CO\textsubscript{2~}treatment and activity traits in the CNS, including
translation initiation factors (\emph{eif3b}, \emph{eif3d}), an
elongation factor (\emph{eef1g}), and ribosomal components
(\emph{rpl23a}, \emph{rpl4},~\emph{rpl7l}, \emph{rps27a}). Genes
involved in protein translocation (\emph{stt3a, rpn1, rpn2, tmed2}), and
protein folding and quality control (\emph{pdia3, pdia4, pdia5, hspa5})
were correlated with CO\textsubscript{2} treatment and behaviours in the
CNS. The endoplasmic reticulum associated degradation (ERAD) pathway
involves protein ubiquitination followed by proteasomal degradation and
we found a range of genes involved in this process to be affected by
CO\textsubscript{2~}treatment. There was small, coordinated upregulation
of genes in the `endoplasmic reticulum' and five ubiquitin-related
functional categories in the CNS, of `proteasome complex' in both
tissues, and of `peptide metabolic process' in the eyes. Genes
positively correlated with CO\textsubscript{2} treatment and all three
activity traits were enriched for `endoplasmic reticulum lumen' and
included genes coding for E3 ubiquitin ligases (\emph{cblb, ttc3}) and a
subunit for the 26S proteasome (\emph{rpn1}). A gene coding for an E3
ubiquitin ligase (\emph{syvn1-} b) was also upregulated in the CNS.
Lysosomal degradation is another method for protein turnover, and a gene
essential for lysosomal function (\emph{ykt6}) was upregulated in both
the CNS and eyes.

3.5.6 Immune function

Genes and functional categories involved in the three stages of the
innate immune response (sensing, signalling and effectors), were
affected by CO\textsubscript{2} treatment in both tissues (Table 5). In
the eyes, the immune sensor molecule \emph{pglyrp2} was downregulated,
while there was small, coordinated upregulation of genes belonging to
the functional category `scavenger receptor activity' which binds
pathogens. Genes that mediate the immune response via cellular
signalling pathways were DE, including upregulation of
\emph{map4k5/3}and \emph{syvn1-b,} and downregulation of \emph{psenen}
in the CNS. In the eyes, there was upregulation of \emph{maoa}, which
plays a key role, via norepinephrine signalling, in the molluscan
neuroendocrine-immune axis-like pathway (Liu \emph{et al.}, 2018; Sun
\emph{et al.}, 2021; Zhou \emph{et al.}, 2011). Genes involved in the
activation and production of immune effectors were also affected by
CO\textsubscript{2~}treatment. In particular, \emph{tf} coding for
transferrin\emph{,} which sequesters iron so it is unavailable for
pathogens and is a key component of the molluscan innate immune
response, including in squid (Herath \emph{et al.}, 2015; Lambert
\emph{et al.}, 2005; Li \emph{et al.}, 2019; Ong \emph{et al.}, 2006;
Salazar \emph{et al.}, 2015), was upregulated and positively correlated
with CO\textsubscript{2} treatment and activity traits in the CNS. The
key molecular marker of autophagy,~\emph{map1l3ca/b}, which plays an
important role in the molluscan immune response (Han \emph{et al.},
2019; Moreau \emph{et al.}, 2015; Picot~\emph{et al.}, 2019) was
downregulated in the CNS. There was also small, coordinated upregulation
of genes belonging to functional categories involved in mediating
phagocytosis, including `cell adhesion' and `integrin complex'. Genes
involved in cell adhesion as part of the immune response (\emph{itga4,
itga9, rac1, ptpr}) were also positively correlated with
CO\textsubscript{2} treatment and activity traits. The cytoskeleton is
also important for phagocytosis and there was small, coordinated
upregulation of genes in three cytoskeleton-related functional
categories in the CNS (`motor activity', `actin binding', and
`microtubule cytoskeleton'), and two downregulated in the eyes
(`cytoskeleton' and `intermediate filament cytoskeleton organisation')
(Figure 4).

3.5.7 Oxidative stress

Genes involved in regulating reactive oxygen species (ROS) and
antioxidant production were differentially expressed in both
issues;~\emph{tf} (CNS: upregulated and positively correlated with
CO\textsubscript{2} treatment and activity traits),
\emph{cyb561d2~}(CNS: downregulated), \emph{cbs} (eyes: upregulated).
Furthermore,~\emph{scl4a11}, which regulates the oxidative stress
response, was positively correlated with CO\textsubscript{2} treatment
and activity traits in the CNS, and there was small, coordinated
downregulation in the CNS of genes involved in `glutathione metabolic
process' (Table 6). Genes and functional categories involved in response
to oxidative damage were also affected by CO\textsubscript{2} treatment
(Table 6). Genes involved in DNA repair were generally upregulated with
CO\textsubscript{2} treatment in the CNS; \emph{chrac1} was
significantly upregulated, there was small, coordinated upregulation of
`damaged DNA binding' and `DNA repair', \emph{spt16, foxm1, bptf,}
and~\emph{arpc5} were positively correlated with
CO\textsubscript{2~}treatment and activity traits, and \emph{nit1} ,
whose loss of expression promotes resistance to DNA damage stress, was
negatively correlated with CO\textsubscript{2} treatment and activity
traits. Genes involved in protein damage control and endoplasmic
reticulum stress were also affected by CO\textsubscript{2} treatment;
\emph{ykt6}, which is essential for autophagy was upregulated in the CNS
and eyes, and the heat shock protein \emph{hspa5}, which is a key
repressor of the unfolded protein response was positively correlated
with CO\textsubscript{2} treatment and activity traits. Furthermore,
genes that induce apoptosis in response to DNA damage (\emph{apbb5}) and
ER stress (\emph{tmem214-b}), were positively correlated with
CO\textsubscript{2} treatment and activity traits. There was also small,
coordinated upregulation in the CNS of genes involved in the `regulation
of apoptotic process'.

\textbf{4. Discussion}

As the nervous system forms the fundamental link between animals and the
environments they inhabit (Kelley~\emph{et al.}, 2018; O'Donnell, 2018),
understanding the neurobiological impacts of environmental change is key
to predicting how and why animals will respond to anthropogenic climate
change. In this study, we sought to understand how projected
end-of-century CO\textsubscript{2} levels alter the nervous system at a
molecular level, and how such changes may affect behaviour of the whole
animal. To do this, we investigated the transcriptomic response to ocean
acidification (OA) of the central and peripheral nervous system of a
marine invertebrate with a complex nervous system, the two-toned pygmy
squid~\emph{Idiosepius pygmaeus}. We then correlated patterns of gene
expression with CO\textsubscript{2} treatment levels and OA-affected
behaviours in the same individuals. The central nervous system (CNS) and
eyes of~\emph{I. pygmaeus} responded to elevated
CO\textsubscript{2~}with significant differential expression (DE) of a
small number of genes, and widespread small, coordinated changes of
genes belonging to important functional categories between
CO\textsubscript{2}conditions. Furthermore, we identified 169 genes in
the CNS, six genes in the eyes and ten genes in both tissues that were
correlated with CO\textsubscript{2} treatment and one or more behaviours
affected by OA, indicating these genes potentially contribute to
OA-induced behavioural changes.

The GABA hypothesis is the predominant mechanistic explanation for
OA-induced behavioural changes in fish (Nilsson \emph{et al.}, 2012;
Tresguerres \& Hamilton, 2017) and may also apply to marine
invertebrates (Thomas \emph{et al.}, 2020). Pharmacological work has
supported the GABA hypothesis in marine molluscs (Clements \emph{et
al.}, 2017; Watson \emph{et al.}, 2014), including in \emph{I.
pygmaeus~}(Thomas \emph{et al.}, 2021). In the whole-body of a pteropod
mollusc, a GABA\textsubscript{A} receptor transcript was upregulated
after OA exposure (Moya \emph{et al.}, 2016). In fish nervous tissue, OA
exposure has variable effects on GABA\textsubscript{A} R subunit
transcript expression, causing upregulation in some species
(Cohen-Rengifo \emph{et al.}, 2022; Schunter \emph{et al.}, 2018) but
not another (Williams\emph{et al.}, 2019). Furthermore, differences in
OA exposure duration (Kang \emph{et al.}, 2022; Schunter \emph{et al.},
2018; Schunter~\emph{et al.}, 2016) and magnitude (Toy \emph{et al.},
2022) are associated with variable effects on the expression of genes
coding for GABA\textsubscript{A} R subunits within species. In \emph{I.
pygmaeus,~}we found small, coordinated downregulation in the CNS and
upregulation in the eyes of genes for ion-channel receptors, which
included GABA\textsubscript{A} receptor subunit transcripts. In the CNS,
there was also upregulation of \emph{syvn1-b} (implicated in
GABA\textsubscript{A}\selectlanguage{greek}α\selectlanguage{english}1 receptor subunit degradation (Crider \emph{et
al.}, 2014; Jiao \emph{et al.}, 2017)), regulators of GABAergic
neurotransmission were positively correlated with
CO\textsubscript{2}treatment and behaviours (\emph{phf24} ,
\emph{rac1}), and \emph{aldh5a1}(involved in the final degradation step
of GABA (Kim \emph{et al.}, 2009)) was negatively correlated with
CO\textsubscript{2} treatment and behaviours. Together, this data
suggests an effect of OA on GABAergic signalling may be widespread,
occurring not only in fish but also marine molluscs, however, effects
may be species and tissue-specific.

Recent research suggests that various other types of neurotransmission
may also be affected by OA and potentially contribute to consequent
behavioural responses. Pharmacological research has identified altered
function of a range of different types of ligand-gated
Cl\textsuperscript{-} channels in \emph{I. pygmaeus} (Thomas \emph{et
al.}, 2021) and the dopamine D1 receptor in a damselfish
(Hamilton~\emph{et al.}, 2023) contributing to OA-induced behavioural
changes. Elevated CO\textsubscript{2} upregulated glycinergic,
cholinergic and glutamatergic transcripts in the whole body of a
pteropod mollusc (Moya~\emph{et al.}, 2016), upregulated glutamatergic
transcripts in the non-nervous tissue of oysters (Ertl \emph{et al.},
2016; Wang \emph{et al.}, 2020), and altered acetylcholine receptor
transcript expression in the whole body of another pteropod mollusc
(Johnson \& Hofmann, 2017). In fish nervous tissue, exposure to OA
conditions caused upregulation of genes coding for glutamatergic and
cholinergic neurotransmission of some species (Cohen-Rengifo \emph{et
al.}, 2022; Schunter \emph{et al.}, 2018; Williams \emph{et al.}, 2019),
but downregulation in others (Kang\emph{et al.}, 2022; Porteus \emph{et
al.}, 2018). In \emph{I. pygmaeus}, we identified small, coordinated
downregulation in the CNS and upregulation in the eyes of genes involved
in neurotransmission mediated by ligand-gated ion channels, including
transcripts for subunits of ionotropic glutamate, glycine and
acetylcholine receptors. There was also small, coordinated
downregulation in the CNS of G protein-coupled receptor (GPCR)-mediated
neurotransmission, including genes for subunits of metabotropic
glutamate, serotonin, dopamine and GABA (GABA\textsubscript{B})
receptors. Key genes for glutamatergic and monoaminergic signalling were
DE, and a subunit of nicotinic acetylcholine receptors (\emph{chrna10})
was correlated with CO\textsubscript{2} treatment and behaviours in both
tissues. Overall, this suggests that OA not only impacts
GABA\textsubscript{A} R function, but various different types of
neurotransmission mediated by ligand-gated ion channels and GPCRs.
However, as with GABAergic signalling, OA effects on other types of
neurotransmission may vary by species and tissue type, and possibly
other factors such as the magnitude and duration of OA exposure. Further
experimentation is needed to understand how OA-induced transcriptomic
responses translate to neurotransmission function and behaviour.

Genes involved in the general processes required for synaptic
neurotransmission were attenuated in the CNS of \emph{I. pygmaeus} after
OA exposure, including Ca\textsuperscript{2+}, K\textsuperscript{+} and
Na\textsuperscript{+} ion channels required for maintenance of membrane
potential, action potential generation and neurotransmitter release.
There was also a negative correlation between the expression of genes
regulating synaptic neurotransmission with CO\textsubscript{2} treatment
and activity traits. Genes for Ca\textsuperscript{2+} and
K\textsuperscript{+} transporters and the regulation of neurotransmitter
release were also downregulated in the brain of spiny damselfish
collected from CO\textsubscript{2} seeps (Kang \emph{et al.}, 2022), but
upregulated after acute and developmental OA exposure (Schunter \emph{et
al.}, 2018), and in fish olfactory tissue after short-term
(Williams~\emph{et al.}, 2019) and transgenerational OA exposure
(Cohen-Rengifo~\emph{et al.}, 2022). These transcriptomic signatures
suggest an even more widespread effect of OA on neurotransmission,
potentially altering the general processes required for synaptic
neurotransmission to occur. However, experimentation is required to
determine functional effects.

Neuroplasticity is the ability of the nervous system to change. Both
neurogenesis (the process by which new neurons are generated and
integrated into existing neural circuits) and synaptic plasticity
(changing of synaptic strength over time) contribute to neuroplasticity
(Costandi, 2016). In the CNS of \emph{I. pygmaeus} we found small,
coordinated upregulation and positive correlation with
CO\textsubscript{2} treatment and activity traits of genes involved in
all the stages required for neurogenesis (re-entering and exiting the
cell cycle, cell proliferation and differentiation to form new neurons,
and neural wiring involving cell migration and adhesion for new neurons
to be incorporated into existing circuits). Widespread upregulation and
positive correlations with CO\textsubscript{2} treatment and behaviours
of genes in the CNS of \emph{I. pygmaeus} involved in transcription, RNA
processing, and protein processing could potentially be a response to
deal with the changed protein demand required due to increased
neuroplasticity. Notably, \emph{cdk10}, which plays an important role in
neurogenesis (Yeh \emph{et al.}, 2013) was identified as correlated with
the OA-induced increase in exploratory interactions in both the CNS and
eyes. Genes involved in synaptogenesis (the formation of new synapses)
and synaptic plasticity were also positively correlated with
CO\textsubscript{2} treatment and OA-affected behaviours in the CNS
of~\emph{I. pygmaeus} .

Despite not assessing the nervous tissue specifically, transcripts
involved in neuronal cell adhesion, neuronal differentiation and
survival and synaptic plasticity were also upregulated in the whole body
of a pteropod mollusc after OA exposure (Moya \emph{et al.}, 2016). In
fish nervous tissue, genes involved in neurogenesis were upregulated in
some species but not others (Lai \emph{et al.}, 2017), and genes
involved in synaptic plasticity were upregulated in some species
(Cohen-Rengifo \emph{et al.}, 2022; Schunter \emph{et al.}, 2018), but
downregulated in another species (Porteus \emph{et al.}, 2018). Thus,
OA-induced transcriptomic responses related to neuroplasticity may be
widespread, occurring in fish and marine molluscs. However, this
response may be taxa-specific and/or could be affected by differences in
CO\textsubscript{2} exposure duration and magnitude that have differed
between studies.

Elevated CO\textsubscript{2} alters the molluscan immune response, with
most research focusing on bivalves (Bibby \emph{et al.}, 2008;
Li\emph{et al.}, 2015; Liu \emph{et al.}, 2016; Su \emph{et al.}, 2018;
Wu~\emph{et al.}, 2016)), though the immune response of an octopus was
also affected by elevated CO\textsubscript{2} (Culler-Juarez \& Onthank,
2021). Here, we found DE of genes that regulate immune signal
transduction pathways and which are also implicated in the molluscan
immune response (\emph{map4k5/3, syvn1-b, psenen} , \emph{cbs})
(Canesi~\emph{et al.}, 2006; De Zoysa \emph{et al.}, 2010; Goodson
\emph{et al.}, 2005; Salazar \emph{et al.}, 2015). There were also
changes in expression of a range of genes that code for immune
effectors, including iron sequestration (\emph{tf} and \emph{cbs}),
autophagy (\emph{map1l3ca/b}), controlling the pool of available
nucleoside triphosphates (\emph{nme6}), and phagocytosis (`cell
adhesion' and multiple cytoskeleton functional categories). Previous
research has also indicated altered phagocytosis in molluscs at elevated
CO\textsubscript{2}; adhesion capacity of haemocytes was decreased in a
clam and expression of integrin (involved in cell adhesion for
phagocytosis) was decreased in an oyster species (Ivanina \emph{et al.},
2014) and increased in another oyster (Ertl \emph{et al.}, 2016).
Furthermore, the phagocytic rate and cytoskeleton component abundance
was decreased, and the expression of cytoskeleton genes was upregulated,
in a clam at elevated CO\textsubscript{2} (Su \emph{et al.}, 2018). Our
results show an effect of OA on the transcriptional profile of genes
implicated in the immune response suggesting OA-induced alterations in
immune function may also occur in molluscan nervous tissue, though
further research directly measuring immune function within the nervous
system is required.

Cross-talk between the neuroendocrine and immune systems coordinates
appropriate physiological and behavioural responses to environmental
change (Demas \emph{et al.}, 2011). In molluscs, neuronal release of
norepinephrine regulates immune responses through a
neuroendocrine-immune axis-like pathway (Liu \emph{et al.}, 2017).
Specifically, changes in the expression and activity of
\emph{maoa~}(upregulated in \emph{I. pygmaeus} eyes here) plays a key
role in immune functioning via norepinephrine in molluscs (Liu \emph{et
al.}, 2018; Sun\emph{et al.}, 2021; Zhou \emph{et al.}, 2011).
Immune-derived factors can also feedback to alter the nervous system and
behaviour (Adamo, 2006; Dantzer \& Kelley, 2007). Indeed, \emph{tf},
which is a key component of the molluscan innate immune response
(Lambert \emph{et al}., 2005\selectlanguage{greek}; \selectlanguage{english}Ong \emph{et al.}, 2006\selectlanguage{greek}; \selectlanguage{english}Herath \emph{et
al.}, 2015\selectlanguage{greek}; \selectlanguage{english}Salazar \emph{et al.}, 2015\selectlanguage{greek}; \selectlanguage{english}Li \emph{et al.}, 2019) was
upregulated and positively correlated with CO\textsubscript{2~}treatment
and activity traits in the CNS of \emph{I. pygmaeus}. We also found the
expression of genes coding for integrins \emph{itga4 and itga9}, cell
adhesion molecules playing a key role in invertebrate immune responses
(Johansson, 1999\selectlanguage{greek}; \selectlanguage{english}Terahara \emph{et al.}, 2006), were positively
correlated in the CNS with CO\textsubscript{2} treatment and activity
traits. Therefore, it is possible that OA-induced changes in
neurotransmission could have consequences on immune function, and
changes in immune function could also feedback on the nervous system to
alter behaviours at elevated CO\textsubscript{2}. However, the potential
links between OA, neurotransmission, immune function and behaviour
remain to be experimentally tested.

Oxidative stress occurs when there is an imbalance between the
production of reactive oxygen species (ROS) and protection by
antioxidant mechanisms (Halliwell \& Gutteridge, 2015). Elevated
CO\textsubscript{2} induces oxidative stress in molluscs, increasing ROS
and altering antioxidant defences inducing DNA damage, lipid
peroxidation and apoptosis (Cao, Liu\emph{, et al.}, 2018; Cao,
Wang\emph{, et al.} , 2018; Kim \emph{et al.}, 2023; Tomanek \emph{et
al.}, 2011; Wang \emph{et al.}, 2016; Zhang \emph{et al.}, 2021).
In~\emph{I. pygmaeus} , we found DE of genes implicated in the
production of antioxidants, including ascorbate and glutathione. We also
identified upregulation in the CNS of genes involved in DNA damage and
repair, protein damage and endoplasmic reticulum stress, and cellular
stress-induced apoptosis. In molluscs, OA exposure has previously been
shown to result in DNA damage (Cao, Liu\emph{, et al.}, 2018;
Nardi~\emph{et al.}, 2018) and increased apoptosis (Cao, Liu\emph{, et
al.}, 2018; Zhang \emph{et al.}, 2021).

The nervous system is particularly vulnerable to oxidative stress
(Halliwell, 2006; Valko \emph{et al.}, 2007) and oxidative
stress-induced damage within the nervous system can disrupt
neurotransmission and neuronal function (Bouayed \emph{et al.}, 2009;
Halliwell, 2006; Halliwell \& Gutteridge, 2015; Lebel \& Bondy, 1991).
In mammals, a link between oxidative stress in the nervous system and
changes in behaviour has been demonstrated (Bhatt \emph{et al.}, 2020;
Bouayed, 2011; Rammal \emph{et al.}, 2010). In the CNS of \emph{I.
pygmaeus} , we identified a positive correlation between the expression
of genes implicated in oxidative stress and
CO\textsubscript{2~}treatment and OA-affected behaviours. In the eyes,
two genes (\emph{crb} , \emph{zranb1}) potentially correlated with
OA-induced behavioural alterations of \emph{I.} \emph{pygmaeus} are
implicated in oxidative-stress induced retinal degeneration (Chartier
\emph{et al.}, 2012; Wang \emph{et al.}, 2018). In particular,
\emph{crb} prevents photoreceptor degeneration by limiting the
production of ROS and the resultant oxidative damage (Chartier \emph{et
al.}, 2012). A recent study in a cuttlefish found the behavioural
effects of OA were associated with an altered retinal structure and an
increase in apoptotic cells within the eyes (Xie \emph{et al.}, 2023).
Thus, it's possible that OA-induced oxidative stress could contribute to
behavioural alterations at elevated CO\textsubscript{2}, potentially
through central and peripheral mechanisms, but further
electrophysiological and whole-animal behavioural experimentation is
required.

When interpreting our results, there are a few important things to
consider. Firstly, despite the reasonable assumption that changes in
gene expression driving behavioural responses occur prior to behavioural
production (Fischer \emph{et al.}, 2021), we measured gene expression
immediately after the OA-induced behavioural responses in \emph{I.
pygmaeus} due to the necessity of terminal sampling to obtain nervous
tissue. Furthermore, the process of transcribing genes is far too slow
to mediate rapid behavioural responses, which are instead mediated by
fast electrical signals passed along and between neurons
(Fischer\emph{et al.}, 2021). Thus, our transcriptomic results do not
describe the neuronal mechanisms driving the immediate behavioural
responses to a stimulus, but rather those that likely contribute to
longer-term changes in behaviour (Clayton \emph{et al.}, 2020; Fischer
\emph{et al.}, 2021) in OA conditions. Secondly, organism responses to
OA can be sex-specific (Ellis \emph{et al.}, 2017), including marine
invertebrate behavioural responses (Mar\selectlanguage{polish}č\selectlanguage{english}eta \emph{et al.}, 2020;
Richardson \emph{et al.}, 2021). We used males only in this study.
Future research could consider using both sexes to determine whether
behavioural responses to OA are sex-specific, and if so whether
differing transcriptional profiles underly these sex-specific responses.

Conclusions

Here, we demonstrate differential expression of specific genes and
widespread small, coordinated changes in expression of genes belonging
to relevant functional categories in the CNS and eyes following
short-term exposure of male~\emph{I. pygmaeus} to OA. We also report
genes correlated with both CO\textsubscript{2} treatment and OA-affected
behaviours, indicating these genes as potentially correlated with
CO\textsubscript{2}-induced behavioural change in~\emph{I. pygmaeus} .
The results identify alterations in the transcriptional profile of genes
implicated in neurotransmission, neuroplasticity, immune function and
oxidative stress. These molecular changes may contribute to OA-induced
behavioural change, as suggested by correlations between gene expression
profiles, CO\textsubscript{2}treatment and OA-affected behaviours. Our
results build on existing knowledge and provide novel hypotheses for
future experiments, including electrophysiological and behavioural
tests, to determine the range of processes responsible for behavioural
changes in marine animals exposed to projected future OA conditions.

\textbf{Acknowledgements}

We thank the technical staff at James Cook University Marine and
Aquaculture Facilities Unit (Ben Lawes, Simon Wever and Andrew
Thompson), and Annam Raza, Natalie Swinhoe and Michael Jarrold for
assistance with the live animal work. We also thank the Breakwater
Marina, Townsville for permission to collect animals within their
premises. Thank you to Carolyn Smith-Keune and Paul O'Brien for
molecular laboratory support and Taewoo Ryu for advice on the
computational analysis. We are grateful for the support provided by the
Scientific Computing and Data Analysis section of Research Support
Division at Okinawa Institute of Science and Technology Graduate
University.

\textbf{Funding}

This work was supported by the Australian Research Council Centre of
Excellence for Coral Reef Studies (PLM, S-AW), an Australian Government
Research Training Program Scholarship (JTT) and the Okinawa Institute of
Science and Technology Graduate University (TR, RH, JTT).

\textbf{Data Accessibility~}

Raw RNA-sequencing and ISO-sequencing data, and the transcriptome
assembly (fasta file) can be found at NCBI BioProject PRJNA798187 (this
is embargoed until peer-reviewed publication) (Thomas~\emph{et al.},~
2022). Raw gene count data, raw water sampling data, all scripts used
for bioinformatic analyses, the annotated transcriptome assembly
(OmicsBox and csv files), R code used for the statistical analyses
(differential expression and gene set analyses), and data files to
accompany the statistical analyses are available from DOI
10.25903/ha66-mm11 (this DOI is embargoed until peer-reviewed
publication) (Thomas~\emph{et al.}, 2023b). All R code for the
statistical analyses (correlating gene expression profiles with
CO\textsubscript{2} treatment and OA-affected behaviours), as well as
accompanying data files for the statistical analyses, can be found at
DOI 10.25903/7dcz-th66 (this DOI is embargoes until peer-reviewed
publication) (Thomas~\emph{et al.}, 2023a).

\textbf{Author Contributions}

Jodi Thomas: \textbf{} Conceptualisation, Methodology, Software, Formal
analysis, Investigation, Resources, Data curation, Writing - original
draft, Writing - review and editing, Visualisation

Roger Huerlimann: \textbf{} Methodology, Software, Writing - review and
editing

Celia Schunter: Conceptualisation, Methodology, Resources, Writing -
review and editing

Sue-Ann Watson: Conceptualisation, Resources, Writing - review and
editing, Supervision

Philip Munday: Conceptualisation, Resources, Writing - review and
editing, Supervision

Timothy Ravasi: Conceptualisation, Methodology, Resources, Writing -
review and editing, Supervision

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